Wednesday, April 10, 2013

5 Reasons Why Banks Must Use Predictive Analysis

Beth Schultz, in her blog post on Predictive Analytics
revealed an interesting story about how her friend was offered refinancing of
her mortgage by her bank, Chase Bank. This was the bank’s reward to her for
being a long standing loyal customer.

How could Chase Bank probably
have arrived at such a decision? The answer lies in Predictive Analysis.

Today,
as banks and financial institutions realize how imperative advanced real-time analytical
solutions are for running their organizations, they are also looking
for constructive predictive analysis tools.

Here are some of the uses of
predictive analysis for banks:

Right Product for the Right Customer:

Using predictive analysis tools,
banks and financial institutions can track individual customers for specific
buying habits and derive a distinctive pattern, using which they can easily
categorize the customers on different parameters and offer them services and
products specific to their needs and wants.

For example: consider that one of
your customers is an NRI, whose account, over a period of time has seen a lot
of transactions for buying or selling of property, indicating that he is
investing heavily in real estate. Perhaps then, wouldn’t a tailor made home
loan with special benefits to NRIs be just the right product for him? This is
also an effective way to decrease customer attrition.

Manage and Maintain Brand Reputation:

Are your twitter streams
bombarded with tweets from dissatisfied customers or is your Facebook wall
filled with negative comments and complaints about your products and services?
Well, left untreated, this negative sentiment could take on giant propositions
and do grave damage to your brand reputation.

Using predictive analysis, banks
can assess the reason for increased negative sentiments about their brands, fix
the issue and thus prevent these instances from snowballing into a PR crisis.

Detect Fraud:

Are some of your customers always
finding their way to the defaulters list? Repeatedly? May be they are not
legitimate customers at all. With Predictive analysis, you can easily find out.

Better Customer Insights:

Banks and financial institutions
nurture a huge repository of customer information both personal and financial. But
the key lies in using this information effectively to increase revenue.

For example: using predictive
analysis, if an IT manager took a home loan and a car loan together but has now
been defaulting every now and then on both EMIs, then may be it is an early
indicator that he could have difficulty repaying both the loans.